Electrochemical and Computational Insights on the Application of Expired Metformin Drug as a Novel Inhibitor for the Sweet Corrosion of C1018 Steel

Ikenna B. Onyeachu, Safwat Abdel-Azeim, Dheeraj Singh Chauhan, Mumtaz A. Quraishi

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An expired metformin drug (MET) was used as a corrosion inhibitor for C1018 carbon steel in a CO2-saturated 3.5wt % NaCl + 340 ppm acetic acid solution under static conditions. The inhibitor was evaluated using electrochemical methods complemented with surface analytical measurements and computational modeling. The drug displayed a high inhibition efficiency of∼90% at 200 ppm. Impedance analyses revealed a rise in the charge transfer resistance at the steel−solution interface upon the addition of the inhibitor. Polarization measurements suggested that MET acted more like a cathodic-type corrosion inhibitor and significantly reduced the corrosion current density. The adsorption of MET on the steel substrate followed the Langmuir isotherm, showing a mixed type of physical and chemical modes of adsorption. The thermodynamic parameters revealed strong and spontaneous adsorption on the steel surface. The surface analysis using SEM supported the inhibitor adsorption on the steel substrate. Based on the DFT simulation, inhibition by MET is mainly achieved by its protonated form, which leads to the formation of a thin film on the steel surface rather than the modification of the work function of the steel surface. The experimental and theoretical estimations of pKa complemented the DFT results, both agreeing that the monoprotonated form of MET is the dominant form in which the inhibitor adsorbs on the steel surface to form a thin film rather than modify the work function of the steel surface.
Original languageEnglish (US)
JournalACS Omega
StatePublished - Dec 23 2020
Externally publishedYes

Bibliographical note

KAUST Repository Item: Exported on 2020-12-28
Acknowledgements: M.A.Q. is thankful for the financial assistance from the KFUPM under the Deanship of Scientific Research (DSR) grant number DF191051. S.A.A. thanks the Supercomputer Shaheen at the King Abdullah University of Science & Technology (KAUST) in Thuwal, Saudi Arabia, for the
permission to use its computational resources.
This publication acknowledges KAUST support, but has no KAUST affiliated authors.


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